Case Study: COVID-19

Irena Papst and Michael Irvine

Model diagram


Susceptible

Exposed

Infectious

Recovered

Model equations

\[\begin{align*} \frac{dS}{dt} &= - \beta S I/N \\ \frac{dE}{dt} &= \beta S I/N - \alpha E \\ \frac{dI}{dt} &= \alpha E - \gamma I \\ \frac{dR}{dt} &= \gamma I \end{align*}\]

Two approaches


covidseir

  • Led by Michael Irvine
  • Data from British Columbia
  • Groups 3 & 4
  • Resources in CaseStudy_Covid19 /covidseir

McMasterPandemic

  • Led by Irena Papst
  • Data from Ontario
  • Groups 5 & 6
  • Resources in CaseStudy_Covid19 /McMasterPandemic

Timeline

Mon-Tue

Work on initial data release

  • Fit with base model
  • “Status quo” forecast
  • Improve fit with model extensions (as time permits)
  • Forecast in response to decision-makers’ request

Wed-Thu

Release of validation data

  • Tweak fits and forecasts
  • Start working on presentation

Fri

Present results

Data

Decision makers’ request

What impact could a mandatory mask policy have on projected case reports?

One rule

Pretend you’re currently living in the time period you’re modelling

  • Go through your instructor for all case data, including hospitalizations and deaths

  • For external sources, do not look at any information beyond the modelling time period